Otto L. Nyquist

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BACKGROUND Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach. RESULTS A data set containing 32(More)
AIMS Cross-sectional serological studies have suggested an association between ischaemic heart disease and infections from Chlamydia pneumoniae and Helicobacter pylori. We therefore sought to find out if patients with ischaemic heart disease had an increased prevalence of C. pneumoniae in the pharynx. As the course of the C. pneumoniae infection remains(More)
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